“So I am going to argue that you need to spend a lot of time focusing on people. This is something I learned from Peter Thiel actually. He used to insist at PayPal that every single person could only do exactly one thing. And we all rebelled, every single person in the company rebelled to this idea. Because it’s so unnatural, it’s so different than other companies where people wanted to do multiple things, especially as you get more senior, you definitely want to do more things and you feel insulted to be asked to do just one thing.

Peter would enforce this pretty strictly. He would say, I will not talk to you about anything else besides this one thing I assigned you. I don’t want to hear about how great you are doing over here, just shut up, and Peter would run away. And then focus until you conquer this one problem. And the insight behind this is that most people will solve problems that they understand how to solve. Roughly speaking, they will solve B+ problems instead of A+ problems. A+ problems are high impact problems for your company but they are difficult. You don’t wake up in the morning with a solution, so you tend to procrastinate them. So imagine you wake up in the morning and create a list of things to do today, there’s usually the A+ one on the top of the list, but you never get around to it. And so you solve the second and third. Then you have a company of over a hundred people so it cascades. You have a company that is always solving B+ things which does mean you grow, which does mean you add value, but you never really create that breakthrough idea. No one is spending 100% of their time banging their head against the wall every day until they solve it. So I highly recommend some version of that. You can be less stringent, you can give people three things to work on, but I would still track the concept of what would happen if you only gave everybody one thing to prioritize.

Traditional “max-spend” policies, whether on travel, meals, office supplies or time-off, often come across as tyrannical and bureaucratic. But most importantly, the encourage a “use it or lose it” mentality that’s at odds with everyone’s best interest.

But the alternative, judgement-driven policies are also not without fault:

Ambiguity– the ambiguity in such policies leads to people constantly questioning their choices. Fear, indecision and abuse, are additional likely side effects. When you can’t tell what’s reasonable, choice becomes a burden, and fearing the consequences of every decision that you make is not real freedom. Choices have a biological cost in the form of “decision fatigue” – a negative impact to the quality of decision making, and overall productivity that we would all rather avoid.

Counter-productive under-spending – Whether as an attempt to minimize the chance of unintentionally over-spending (and suffering the consequences as a result), or due to some people’s natural tendency to frugality, and other psychological biases (like a misguided hero syndrome), counter-productive under-spending in not unlikely. Under-spending on a client dinner, taking a 3-connections flight, or not taking enough time-off can all result in negative implications to the business.

Is there a way to avoid the short-comings of both “max-spend” and “judgement-based” policies?

Dan argues that the answer is “yes”, through designing policies that adhere to these two principles:

Provide benchmarks – use historical data to provide a relevant guideline for “what’s reasonable”. For example: “on average, employees spend $xxx/night, when booking hotels in city X”. Providing an anchoring point for “what’s reasonable” reduces fear and decision fatigue while leaving the door open for varying from the average for a good reason.

Set minimum guardrails – a “minimum-spend” guideline, can reduce the risk of counter-productive under-spending, without encouraging a “use it or lose it” mentality.

This perspective strongly resonates with me, and looking at various organizations through this lens reveals a very interesting opportunity. In many organizations, these systems are managed in one of two ways:

Either in a completely grassroots, ad-hoc, organically evolving manner. (the Shadow IT phenomenon comes to mind)

Or in a completely top-down manner, being wholly owned and operated by a functional department (IT, HR, etc.) with sole authority to make changes to the system.

Neither of those approaches work well. While the former often leads to increased variability and complexity that poses massive constraints on scaling the systems, the latter often leads to stale, disjointed systems with very limited flexibility and adaptability. In both cases, over time, the systems become less effective in driving the desired business outcomes.

If you are a software developer, this may start to sound all too familiar. Because, the problems the exist in organizational systems and the way they are managed, are very similar to problems the exist in software systems and the way they are managed.

Fortunately, this also means that we can draw on the parallels in the software world for potential solutions, to enable the broader community of employees to contribute to the on-going evolution of these systems while at the same time, not jeopardizing their structural integrity and effectiveness.

Enter the role of a “system architect”, as the good folks at Spotify describe it (they call it a “system owner”):

“The System [Architect] is the go-to person for any technical or architectural issues related to that system. He is a coordinator who guides people who [modify] that system to ensure that they don’t stumble over each other. He focuses on things like quality, documentation, technical debt, stability, scalability and [change management] process. The System Architect is not a bottleneck or an ivory tower architect. He does not personally have to make all decisions, or [make all modifications], or [handle all change management efforts]… We also have a Chief Architect role, a person who coordinates work on high-level architectural issues that cut across multiple systems. He reviews development of new systems to make sure they avoid common mistakes, and that they are aligned with our architectural vision”.

One of the key challenges with adopting this systems approach to the various organizational components, is that it significantly raises the bar for the role that the “traditional” owners of those systems are expected to play in the ongoing evolution and management of those systems. However this, in my mind, is an investment that is well worth making.

In a nutshell, it’s about 70% one of the best People Operations books that you’ll ever read, and 30% a healthy overdose of the Google Kool-Aid. The former makes the latter completely worthwhile.

My two biggest takeaways:

The impact of the rigorous scientific, data-driven approach to figuring out the answers for some of the biggest people questions, like “do we really need managers?”, for example. Often times coming out with an answer that’s very different from the common wisdom. Yes, every organization and company are different. But they are more similar than we think. Starting from a “tried and true” blueprint and then modifying it to the unique aspects of your organization, is a much better strategy than reinventing the whole thing from scratch. And to that end, the Google blueprint is a much better starting point than many of the more traditional HR practices.

The impact of a people operations system that’s tied to a coherent set of overarching principles. This one is really hard to grok without reading the book, but being the visual thinker that I am, I tried to distill it into a mind-map, primarily for my own benefit, but others may find it useful as well: